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Functional normalizations for the branching process with infinite mean

Published online by Cambridge University Press:  14 July 2016

Andrew D. Barbour*
Affiliation:
Gonville and Caius College, Cambridge
H.-J. Schuh
Affiliation:
CSIRO Division of Mathematics and Statistics, Canberra
*
Postal address: Statistical Laboratory, 16 Mill Lane, Cambridge CB2 1SB, U.K.

Abstract

It is well known that, in a Bienaymé-Galton–Watson process (Zn) with 1 < m = EZ1 < ∞ and EZ1 log Z1 <∞, the sequence of random variables Znm –n converges a.s. to a non–degenerate limit. When m =∞, an analogous result holds: for any 0< α < 1, it is possible to find functions U such that α n U (Zn) converges a.s. to a non-degenerate limit. In this paper, some sufficient conditions, expressed in terms of the probability generating function of Z1 and of its distribution function, are given under which a particular pair (α, U) is appropriate for (Zn). The most stringent set of conditions reduces, when U (x) x, to the requirements EZ1 = 1/α, EZ1 log Z1 <∞.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1979 

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Footnotes

∗∗

Present address: Department of Statistics, Richard Berry Building, University of Melbourne Parkville, Victoria 3052, Australia.

References

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